Modelling Strong Ground Motions for Subduction Events in the Wellington Region, New Zealand

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1 Proceedings of the Ninth Pacific Conference on Earthquake Engineering Building an Earthquake-Resilient Society April, 2011, Auckland, New Zealand Modelling Strong Ground Motions for Subduction Events in the Wellington Region, New Zealand C. Holden & J.X. Zhao GNS Science, Lower Hutt, Wellington. ABSTRACT: The work presented here is focused on simulating ground motions from potential large plate boundary subduction thrust earthquakes at specified locations in the Wellington region in terms of response spectra and acceleration time histories. We employ the methodology of Irikura et al. (2004) and validate their code and procedures using the strong motion dataset from the 2003 M w 7.2 Fiordland earthquake applying both empirical and stochastic Green s functions. The method was satisfactorily tested using an intraslab rupture and a record from a nearby aftershock as the empirical Green s function (EGF). For the stochastic Green s functions (SGF) approach, we adopt the work of Motazedian & Atkinson (2005) because we consider their assumption of a finite fault source model (instead of a point source) is more appropriate in the Wellington case where events have magnitudes > 5, and distances < 200 km. We are currently applying these techniques to a number of source scenarios that sample a range of plausible subduction interface ruptures underneath Wellington. Key parameters that we vary are hypocentre location, stress drop, and overall rupture area. In addition, recent advances in detailed modelling of the Wellington basin geology will allow us to include site effects in our simulated ground motion results. 1 BROADBAND GROUND MOTION MODELLING 1.1 Introduction The It s Our Fault programme aims to position Wellington as a more resilient city through a comprehensive study of the likelihood of large Wellington earthquakes, the effects of these earthquakes, and their impacts on humans and the built environment (Van Dissen et al. 2009, 2010). The work presented here is a component of that programme. The Wellington region is underlain by the west-dipping subduction interface between the Pacific and Australian plates. Lack of definitive historical precedent and/or geological evidence regarding the earthquake-generating potential of the subduction mega-thrust under Wellington, and the lack of empirical ground-motion data from this mega-thrust (and similar ones globally where the potential seismogenic zone is onshore, not out at sea) severely hinders our ability of characterise the hazard and risk posed by this, potentially, the largest earthquake source in New Zealand. To address a component of this uncertainty, we have embarked on an investigation to derive simulated ground motions resulting from various plausible Wellington subduction zone rupture scenarios. In the pages that follow, we present results to date. 1.2 Methods Earthquake demands on a structure are commonly derived from empirical models (McVerry et al. 2006), through either a probabilistic seismic hazard study or a deterministic assessment. Structural designers then use strong-motion records selected from a world-wide database with appropriate magnitude and distance combinations, and suitable site conditions, which are scaled to match a design spectrum. Often, it is not possible to select/find a record with all desired characteristics. This is certainly the case for Wellington in relation to its underlying subduction mega-thrust. Recent Paper Number 229

2 developments in numerical simulation provide an alternative approach for deriving ground motions that can account for detailed fault rupture processes (including forward and backward directivity effects), complex propagation paths, and the location of the site relative to a specific fault of interest. Three codes are commonly used to model broadband ground motion: the empirical Green s function method, the stochastic Green s function method and the purely stochastic approach. To test the codes against a New Zealand dataset, we modelled the Mw 7.2 Fiordland event, using the empirical Green s function (EGF) code developed by Irikura (1986) with the recipe developed by Irikura et al. (2004). The empirical Green s functions use recorded motions at the site of interest from small earthquakes close to the target source zone of the large event that it is desired to model, to capture path and site effects for the source and site combination. The synthetic seismograms are computed by summation of each individual small event on the fault plane, following scaling relationships relating the main shock to the small events. The alternative to using EGF is the stochastic Green s functions (SGF) approach, which we also tested against the Mw 7.2 Fiordland event dataset. A time series simulated with a stochastic method (e.g. Boore, 1983) has a stochastic character (Gaussian noise and zero mean and unit variance) and spectrum amplitude constrained by the earthquake characteristics such as moment, corner frequency and stress drop. This method is more appropriate due to the lack of earthquake records in the Wellington region. The Motazedian & Atkinson (2005) approach, implemented in the EXSIM code, extended the stochastic point source model from Boore (1983) to finite fault modelling by summing individual point sources with the proper time delay. Finally, we computed broadband seismograms for a range of plausible large subduction events under Wellington using a purely stochastic approach to start with; we also plan to compute seismograms using the stochastic Green s function approach to create a database as complete as possible. 2 CASE STUDY: THE M W 7.2 FIORDLAND EARTHQUAKE 2.1 Background In order to test and validate ground motion modelling codes and methodologies in a New Zealand subduction context, we chose to work with the 2003 Fiordland event dataset (Figure 1). The M w Fiordland earthquake was the largest and best recorded subduction event in New Zealand at the time that this study was initiated. New Zealand has since experienced a larger subduction event, the M w Dusky earthquake, which will also be modelled later on. We employ the methodology of Irikura et al. (2004) and validate their code and procedures using this dataset and applying both empirical and stochastic Green s function approaches. An ideal Green s function is 2 orders of magnitude smaller than the main shock, has rupture mechanism, depth and location similar to the main shock ones, and is recorded at a set of welldistributed stations around the epicentre. The Mw 7.2 Fiordland event was followed by many aftershocks and one of them, named aftershock 5, was a perfect candidate (Figure 1): a magnitude of 5.5, and a rupture mechanism and depth similar to the mainshock ones, as described below: Strike 216, dip 24 and rake 91 ; 27 km. (M w 5.5) Strike 215 dip 64 and rake 93 ; 24 km. (M w 7.2) We used records from aftershock 5 as our empirical Green s functions to construct a simulated M w 7.2 event. We then compute ground motions that would be generated by this simulated M w 7.2 event and compare them with the ground motions that were actually recorded for the M w 7.2 Fiordland event. We do this to test the suitability of the modelling technique and codes we have chosen (Irikura et al. 2004, Irikura 1986, Motazedian and Atkinson, 2005). If the fit is good between the simulated results and the actual recorded data, it provides confidence that the methodology, if applied to Wellington, will yield realistic and useful results. 2

3 Figure 1: M w Fiordland event (red) and its aftershocks (grey) ; the figure also shows the nearby strongmotion stations as well as recent regional large events such as the 2009 M w 7.6 Dusky earthquake (black). 2.2 Modelling with Empirical Green s Function ( aftershock 5 ) We first test the Irikura at al. (2004) recipe using Aftershock 5 as an empirical Green s function (EGF). We present the results for stations MANS and MSZS, at closest distances of 50 km and 100 km from the rupture zone of the mainshock. The EGF approach produced satisfactory peak ground acceleration, velocity and displacement as well as the duration of the signals (Fig. 2). The response spectra are also very similar as shown in Figure 2 for station MANS, except at 0.12 seconds where the synthetic spectrum is lower than the recorded one, indicating that stress drop in the model may be too low. The predicted spectra in the period range of seconds are larger than the observed ones, indicating that the size of the source is likely to be smaller than the one modelled. Figure 2: Results from empirical Green s function modelling at station MANS for the M w 7.2 mainshock - left: acceleration (mm/s 2 ) and displacement (mm) time histories for 2 horizontal components; right: displacement and acceleration spectra. 2.3 Modelling with Stochastic Green s Function We then test the Irikura at al. (2004) recipe using a stochastic model of Aftershock 5, consequently becoming a stochastic Green s function (SGF). Although the Fiordland event generated many aftershocks, it was difficult to find small events suitable for EGF methodology (that is, events that were: i) 2 magnitude units smaller than the mainshock, ii) recorded at a well distributed set of stations, and iii) with a rupture mechanism similar to the mainshock). The situation is even worse for our modelled area in It s Our Fault programme, the 3

4 Wellington region. We investigated the use of an alternative approach to generate the Green s functions. For this we adopted the stochastic approach of Motazedian & Atkinson (2005) to generate our Green s functions as explained earlier. We have successfully generated synthetic accelerograms for aftershock 5 at two stations MANS and MSZS. We then used the stochastic Green s function to compute accelerograms for the 2003 Fiordland event combined with the Irikura et al. (2004) recipe. Figure 3 shows that the generated accelerograms have very similar amplitude and durations to those of the strong-motion records. The acceleration response spectra match the recorded ones better than the empirical approach (Fig. 3), especially at the high frequency end of the spectra. Figure 3: observed (blue) and synthetic (red) accelerograms (left) and response spectra (right) at station MANS using a stochastic Green s function 3 SIMULATING GROUND MOTIONS FOR WELLINGTON SUBDUCTION EVENTS 3.1 Background A recent study by Wallace & Beavan (2010) has delineated the location and extent of the currently locked region on the subduction interface under Wellington (Fig. 4). For our study, we take the locked region as representing the dimensions of a potential rupture area for great mega-thrust earthquakes. We treat his locked area via two different scenarios. The first rupture area scenario, equivalent to a magnitude 8.2, occurs beneath Wellington and ruptures eastward up to a depth of 15km. The second scenario assumes that the rupture does not stop at 15 km but instead propagates further east to a depth of 5 km and is equivalent to a magnitude 8.6 earthquake. Two characteristic scenarios are modelled with varying overall rupture area and location following the recent findings from Wallace & Beavan (2010) and discussions with Wallace and McVerry (pers. comm.). Both have a 225 strike and a 10 dip to the NW, consistent with the regional tectonic context (Fig. 4). To start with, we used a purely stochastic approach, and the EXSIM code developed by Motazedian and Atkinson (2005), and this is the work reported on below; however the final simulated ground motion database will also include seismograms computed with the stochastic Green s function approach. We modelled a number of scenario events for 35 rock sites at a grid spacing of 5 km, covering the Wellington region. Broadband seismograms were calculated for frequencies up to 25 Hz at all these sites. Preliminary results are presented in the form of peak ground acceleration (PGA) maps (e.g. Fig. 5). We modelled the effects of various rupture scenarios by varying the magnitude of the events, the rupture initiation location and the stress drops. The variable parameters are as follow: Two magnitude values: 8.2 and 8.6, three stress drop values: 30, 90 and 150 bars, and three rupture 4

5 initiation locations: bottom of the fault plane, top north and top south corners. 3.2 Large subduction events with various magnitudes In Figures 5a & 5b we present preliminarily ground motion results for the two different sized rupture areas using identical stress drops for the two sources of 90 bars, and both having ruptures that initiate at the centre of the fault plane. For the magnitude 8.2 event, the peak ground accelerations (PGAs) at Wellington sites range between 76 and 173 cm/s 2 (Fig. 5a). For the magnitude 8.6 scenario, the maximum PGA is 493 cm/s 2 (Fig. 5b). The PGAs for the magnitude 8.6 event are three times larger than those for the magnitude 8.2 scenario. Figure 4 Left: Fault locking using campaign GPS velocities (last ~15years). Green contours show total slip on the interface in slow slip events since 2002 (from Wallace & Beavan 2010) Right: simplified representations of two plausible Wellington subduction mega-thrust scenarios: the rupture area for the magnitude 8.2 scenario is shown in blue, and the magnitude 8.6 scenario in shown in orange. Black stars represent rupture initiation locations at northern and southern corners, and the yellow star at the bottom side of the fault plane, as explained in section Large subduction events with various rupture initiation location We then modelled the effects of varying the rupture initiation location. For all these runs, we used a stress drop of 90 bars, and the magnitude of 8.2 rupture area, but varied the rupture initiation point (bottom of rupture plane, and north and south ends of rupture plane, black stars on Fig. 4). The maximum PGA s are very similar for the three considered initiation scenarios: 173 cm/s 2 for the bottom starting point, 198 and 128 cm/s 2 for a rupture starting at the northern and southern end respectively. 3.4 Large subduction events with various stress drops In a stochastic modelling approach, stress drop controls the level of spectra at high frequencies, and does not influence the moment magnitude of the modelled earthquake (Motazedian and Atkinson, 2005). We modelled a range of stress drop values from as low as 30 bars to as much as 150 bars, following Atkinson et al. (2009) study of the variability of stress drop on worldwide subduction events. The resulting PGAs show considerable variation with maximum PGA of 83, 173 and 242 cm/s 2 for stress drops of 30, 90 and 150 bars respectively (Figs 5a, 5c & 5d). As highlighted in Atkinson et al. (2009), stress drop is a major contributing factor in shaking intensity, illustrated here with amplification factors up to 3 times between the lowest and highest considered stress drop values. 5

6 a) M w 8.2 event 90 bars stress drop b) M w 8.6 event 90 bars stress drop c) M w 8.2 event 30 bars stress drop a) M w 8.2 event 150 bars stress drop Figure 5: PGA maps in Wellington for various magnitude and stress drop subduction events Figure 6 compares the response spectra computed from the models that gives the upper and lower limits among all the scenarios with the 500-year design spectra of the current design code for a rock site in Wellington. The red line is for the spectrum from the worst modelling scenario and the lower blue line is for the best scenario. The spectral shapes for the three synthetic spectra are quite similar and the synthetics are lower than the code spectrum at short periods. At long periods over about 2s, the synthetic spectra are considerably higher than the code spectra even for the best scenario. For the worst scenario, the synthetic spectrum is much higher than the code spectrum at periods over about 0.5s. A striking feature of the synthetic spectra is that the slopes of the spectra at periods longer than the plateau of the spectrum are nearly identical to that of the code spectrum (1/T where T is spectral period, constant velocity spectrum), while the code spectrum at periods over 3s (1/T 2 constant displacement spectrum) is much lower than the synthetic spectra, even for those from the best modelling scenario. This feature is not surprising because the spectral period where the constant velocity spectrum ends and constant displacement spectrum starts for an earthquake with a magnitude over 8 is likely to be over 10s (Abrahamson et al., 2008). The value of 3s in the McVerry et al. (2006) model was a result of few strong-motion records in New Zealand that can be used beyond 3s spectral period. Of the subduction mega-thrust rupture scenarios considered so far, the strongest ground motions are generated from our magnitude 8.6 event rupturing downdip with a large stress drop, leading to estimated maximum PGAs of 716 cm/s 2 ; the scenario that generates the lowest PGAs, in this particular case study, is a magnitude 8.2 or 8.6 event, rupturing updip with a low stress drop. This scenario would bring maximum PGAs of 83 and 238 cm/s 2 respectively. 6

7 10 Spectral acceleration (g) Code spectra 500 years Average spectrum (Mw stress drop 90bars) Average spectrum (Mw stress drop 150bars) code Spectrum 1000 year Average Spectrum (Mw stress drop 30 bars) Spectral period (s) Figure 6: comparison of spectral accelerations for the New Zealand code spectra and various magnitude and stress drops scenarios for modelled Wellington subduction mega-thrust ruptures. 4 FUTURE PLANNED INVESTIGATIONS To date, we have been able to apply various broadband ground motion modelling techniques to a New Zealand context. The Irikura approach has proven to be efficient in reproducing the M w 7.2 Fiordland earthquake ground motions using both an empirical and a stochastic Green s function. The purely stochastic approach has been employed to test two plausible subduction magnitude scenarios with various rupture parameters, and concluded that the most likely one (low stress drop, updip rupture) would be the least intense one in terms of PGAs in Wellington. We would also like to compute broadband ground motions using the stochastic Green s function approach to create a database as robust as possible. REFERENCES: Abrahamson, N. A. and Silva, W. J Summary of the Abrahamson & Silva NGA Ground-Motion Relations, Earthquake Spectra, 24(1), Atkinson, G., and M. Macias Predicted ground motions for great interface earthquakes in the Cascadia subduction zone, Bulletin of the Seismological Society of America 99. no. 3, Atkinson, G., K. Assatourians, D. Boore, K. Campbell, and D. Motazedian A guide to differences between stochastic point-source and stochastic finite-fault simulations. Bulletin of the Seismological Society of America 99. 3,192 3,201 Boore, D Stochastic simulation of high-frequency ground motions based on seismological models of the radiated spectra, Bulletin of the Seismological Society of America Irikura, K Prediction of strong acceleration motion using empirical Green's function, Proceedings of the 7th Japan Earthquake Symposium Irikura, K., H. Miyake, T. Iwata, K. Kamae, H. Kawabe, and L. A. Dalguer Recipe for predicting strong ground motion from future large earthquake, Proceedings of the 13th World Conference on Earthquake Engineering. Paper No McVerry, G.H.; Zhao, J.X.; Abrahamson, N.A.; Somerville, P.G New Zealand acceleration response spectrum attenuation relations for crustal and subduction zone earthquakes. Bulletin of the New Zealand Society for Earthquake Engineering, 39(1): 1-58 Motazedian, D., and G. M. Atkinson 2005a. Stochastic finite-fault modelling based on a dynamic corner frequency. Bulletin of the Seismological Society of America Van Dissen R., and 27 others It s Our Fault: Better Defining the Earthquake Risk in Wellington - Results 7

8 to Date & a Look to the Future. Proceedings 2009 NZSEE conference, Christchurch, NZ. Van Dissen, R.J., and 37 others It s Our Fault: better defining earthquake risk in Wellington. In Williams, A.L., Pinches, G.M., Chin, C.Y., McMorran, T.J. & Massey, C.I. (eds). Geologically active: delegate papers 11 th Congress of the International Association for Engineering Geology and the Environment, 5-10 September 2010, Auckland, New Zealand: CRC Press. Wallace, L.M.; Beavan, R.J Diverse slow slip behavior at the Hikurangi subduction margin, New Zealand. Journal of geophysical research. Solid earth. 115: B12402, doi: /2010jb Acknowledgements: It s Our Fault is jointly funded by EQC, ACC, Wellington City Council, Wellington Region Emergency Management Group, Greater Wellington Regional Council and Natural Hazards Research Platform; we are indebted for their support. We wish to thank Russ Van Dissen and Graeme McVerry for the reviews of the manuscript. 8